Design and evaluation of a wearable vascular interventional surgical robot system

BACKGROUND

Remote-controlled robotic vascular interventional surgery can reduce radiation exposure to interventional physicians and improve safety. However, inconvenient operation and lack of force feedback limit its application.

MATERIALS AND METHODS

A new wearable robotic system for vascular interventional surgery is designed, which is more flexible in operation. It ensures the safety of surgery through haptic force feedback. The system was evaluated by human vascular models and animal experiments.

RESULTS

The average static error of the system is 0.048 mm when the axial motion is 250 mm and 1.259° when the rotational motion is 400°. The average error of the force feedback is 0.021 N. The results of vascular model experiments and animal experiments demonstrate the feasibility and safety of the system.

CONCLUSIONS

The proposed robotic system can assist physicians in remotely delivering standard catheters or guidewires. The system is more flexible and uses haptic force feedback to ensure surgical safety.

Teleoperated Surgical Robot with Adaptive Interactive Control Architecture for Tissue Identification

The remote perception of teleoperated surgical robotics has been a critical issue for surgeons in fulfilling their remote manipulation tasks. In this article, an adaptive teleoperation control framework is proposed. It provides a physical human-robot interaction interface to enhance the ability of the operator to intuitively perceive the material properties of remote objects. The recursive least square (RLS) is adopted to estimate the required human hand stiffness that the operator can achieve to compensate for the contact force. Based on the estimated stiffness, a force feedback controller is designed to avoid the induced motion and to convey the haptic information of the slave side. The passivity of the proposed teleoperation system is ensured by the virtual energy tank. A stable contact test validated that the proposed method achieved stable contact between the slave robot and the hard environment while ensuring the transparency of the force feedback. A series of human subject experiments was conducted to empirically verify that the proposed teleoperation framework can provide a more smooth, dexterous, and intuitive user experience with a more accurate perception of the mechanical property of the interacted material on the slave side, compared to the baseline method. After the experiment, the design idea about the force feedback controller of the bilateral teleoperation is discussed.

Design and evaluation of vascular interventional robot system for complex coronary artery lesions

At present, most vascular intervention robots cannot cope with the more common coronary complex lesions in the clinic. Moreover, the lack of effective force feedback increases the risk of surgery. In this paper, a vascular interventional robot that can collaboratively deliver multiple interventional instruments has been developed to assist doctors in the operation of complex lesions. Based on the doctor's skills and the delivery principle of interventional instruments, the main and slave manipulators of the robot system are designed. Haptic force feedback is generated through resistance measuring mechanism and active drag system. In addition, a force feedback control strategy based on force-velocity mapping is proposed to realize the continuous change of force and avoid vibration. The proposed robot system was evaluated through a series of experiments. The experimental results show that the system can accurately measure the delivery resistance of interventional instruments, and provide haptic force feedback to doctors. The capability of the system to collaboratively deliver multiple interventional instruments is effective. Therefore, it can be considered that the robot system is feasible and effective.

Technical and Clinical Progress on Robot-Assisted Endovascular Interventions: A Review

Prior methods of patient care have changed in recent years due to the availability of minimally invasive surgical platforms for endovascular interventions. These platforms have demonstrated the ability to improve patients' vascular intervention outcomes, and global morbidities and mortalities from vascular disease are decreasing. Nonetheless, there are still concerns about the long-term effects of exposing interventionalists and patients to the operational hazards in the cath lab, and the perioperative risks that patients undergo. For these reasons, robot-assisted vascular interventions were developed to provide interventionalists with the ability to perform minimally invasive procedures with improved surgical workflow. We conducted a thorough literature search and presented a review of 130 studies published within the last 20 years that focused on robot-assisted endovascular interventions and are closely related to the current gains and obstacles of vascular interventional robots published up to 2022. We assessed both the research-based prototypes and commercial products, with an emphasis on their technical characteristics and application domains. Furthermore, we outlined how the robotic platforms enhanced both surgeons' and patients' perioperative experiences of robot-assisted vascular interventions. Finally, we summarized our findings and proposed three key milestones that could improve the development of the next-generation vascular interventional robots.

A Deep-Learning-Based Guidewire Compliant Control Method for the Endovascular Surgery Robot

Endovascular surgery is a high-risk operation with limited vision and intractable guidewires. At present, endovascular surgery robot (ESR) systems based on force feedback liberates surgeons' operation skills, but it lacks the ability to combine force perception with vision. In this study, a deep learning-based guidewire-compliant control method (GCCM) is proposed, which guides the robot to avoid surgical risks and improve the efficiency of guidewire operation. First, a deep learning-based model called GCCM-net is built to identify whether the guidewire tip collides with the vascular wall in real time. The experimental results in a vascular phantom show that the best accuracy of GCCM-net is 94.86 ± 0.31%. Second, a real-time operational risk classification method named GCCM-strategy is proposed. When the surgical risks occur, the GCCM-strategy uses the result of GCCM-net as damping and decreases the robot's running speed through virtual resistance. Compared with force sensors, the robot with GCCM-strategy can alleviate the problem of force position asynchrony caused by the long and soft guidewires in real-time. Experiments run by five guidewire operators show that the GCCM-strategy can reduce the average operating force by 44.0% and shorten the average operating time by 24.6%; therefore the combination of vision and force based on deep learning plays a positive role in improving the operation efficiency in ESR.

An Endovascular Catheterization Robotic System Using Collaborative Operation with Magnetically Controlled Haptic Force Feedback

Robot-assisted technology is often used to perform endovascular catheterization surgeries, which generally depend on the flexible operability and the accurate force feedback of a robotic system. In this paper, an endovascular catheterization robotic system (ECRS) was developed to improve collaborative operation and haptic force feedback. A couple of operating handles were designed to maximize the use of the natural operations of surgeons on the master side, which is a flexible and ergonomic device. A magnetically controlled haptic force feedback structure is proposed based on hydrogel and solid magnetorheological (MR) fluid to offer a sense of haptic feedback to operators; this has potential influence on the field of force feedback. In addition, a unique tremor-reduction structure is introduced to enhance operating safety. Tracking performance experiments and in vitro experiments were conducted to evaluate the performance of the developed ECRS. According to these experimental results, the average translation-tracking error is 0.94 mm, and the average error of rotation is 0.89 degrees. Moreover, in vitro experiments demonstrated that haptic feedback has the advantage of reducing workload and shortening surgery completion time. The developed ECRS also has the benefits of inspiring other researchers to study collaborative robots and magnetically controlled feedback.